Thomas W. Gauperaa @gauperaa - Twitter Profile

1 day ago

@RonEisenmann He did what is probably best for Nato, to be in Trump's good graces by praising him, and at the same getting across that NATO creates jobs in the US

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Thomas W. Gauperaa @gauperaa

16 days ago

@OldWoofer02 @Logically_JC Norway is a *social democracy*. From wikiwand: "In modern practice, social democracy has taken the form of a predominantly capitalist, yet robust welfare state, with policies promoting social justice, market regulation, and a more equitable distribution of income."

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Thomas W. Gauperaa @gauperaa

3 months ago

@camillamonk @Acyn Lol, I was thinking about Starship Troopers too :D

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Thomas W. Gauperaa @gauperaa

3 months ago

@everymovieplug Cool looking, but I don't really care since it is lacking tension – it doesn't feel like he is risking anything

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Who to follow

Graham Faithfull

@stourvalewalker

I enjoy lightweight backpacking.

petesy

@petesy

Still the same stuff, just not on here. Find me in the other obvious venues, I'm done with this place.

Thomas W. Gauperaa @gauperaa

4 months ago

@ericweinstein https://t.co/sLyzjivlMO

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Thomas W. Gauperaa @gauperaa

4 months ago

@MarcelDeneuve Love it! And so nice to see something real and original and not the AI slop

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Thomas W. Gauperaa @gauperaa

4 months ago

@ashebytes What a great looking cappuccino, bet it was tasty 😍

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gauperaa retweeted

Just Jack

@7Veritas4

4 months ago

Be right back. Gonna punch my neighbor before he can punch me back for punching him.

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Thomas W. Gauperaa @gauperaa

4 months ago

@247_365Football @DearthOfSid SNL has a hard time beating reality 😅

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Thomas W. Gauperaa @gauperaa

4 months ago

@DannyLimanseta I actually think I prefer the original, it seems more real

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Thomas W. Gauperaa @gauperaa

4 months ago

@exQUIZitely I did, great game!

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gauperaa retweeted

Alex Veremeyenko

@alex_verem

4 months ago

Anthropic's own researchers just proved that using AI to learn new skills makes you 17% worse at them. and the part nobody's reading is more important than the headline. the paper is called "How AI Impacts Skill Formation." randomized experiment. 52 professional developers. real coding tasks with a Python library none of them had used before. half got an AI assistant. half didn't. the AI group scored 17% lower on the skills evaluation. Cohen's d of 0.738, p=0.010. that's a real effect. and here's what makes it sting: the AI group wasn't even faster. no significant speed improvement. they learned less AND didn't save time. but the viral framing of "AI bad for learning" misses what actually matters in this paper. the researchers watched screen recordings of every single participant. they identified 6 distinct patterns of how people use AI when learning something new. 3 of those patterns preserved learning. 3 destroyed it. the gap between them is enormous. participants who only asked AI conceptual questions scored 86% on the evaluation. participants who delegated everything to AI scored 24%. same tool. same task. same time limit. the difference was cognitive engagement. the highest-scoring AI users actually outperformed some of the no-AI group. they asked "why does this work" instead of "write this for me." they generated code then asked follow-up questions to understand it. they used AI as a thinking partner, not a replacement for thinking. the lowest-scoring group did what most people do under deadline pressure: pasted the prompt, copied the output, moved on. they finished fastest. they learned almost nothing. and here's the finding that should concern every engineering manager alive: the biggest score gap was on debugging questions. the skill you need most when supervising AI-generated code is the exact skill that atrophies fastest when you let AI do the work. the control group made more errors during the task. they hit bugs. they struggled with async concepts. they got frustrated. and that struggle is precisely what built their understanding. errors aren't obstacles to learning. they ARE learning. removing them with AI removes the mechanism that creates competence. participants in the AI group literally said afterward they wished they'd "paid more attention" and felt "lazy." one wrote "there are still a lot of gaps in my understanding." they could feel the hollowness of having completed something without understanding it. that's not a productivity win. that's debt. this paper isn't an argument against using AI. it's an argument against using AI unconsciously. Anthropic publishing research showing their own product can inhibit skill formation is the kind of intellectual honesty the industry needs more of. the practical takeaway is simple: if you're learning something new, use AI to ask questions, not to skip the work. the struggle is the product.

alex_verem's tweet photo. Anthropic's own researchers just proved that using AI to learn new skills makes you 17% worse at them.

and the part nobody's reading is more important than the headline.

the paper is called "How AI Impacts Skill Formation." randomized experiment. 52 professional developers. real coding tasks with a Python library none of them had used before. half got an AI assistant. half didn't.

the AI group scored 17% lower on the skills evaluation.

Cohen's d of 0.738, p=0.010.

that's a real effect.

and here's what makes it sting: the AI group wasn't even faster.

no significant speed improvement. they learned less AND didn't save time.

but the viral framing of "AI bad for learning" misses what actually matters in this paper.

the researchers watched screen recordings of every single participant.

they identified 6 distinct patterns of how people use AI when learning something new.

3 of those patterns preserved learning. 3 destroyed it.

the gap between them is enormous. participants who only asked AI conceptual questions scored 86% on the evaluation.

participants who delegated everything to AI scored 24%.

same tool. same task. same time limit.

the difference was cognitive engagement.

the highest-scoring AI users actually outperformed some of the no-AI group. they asked "why does this work" instead of "write this for me."

they generated code then asked follow-up questions to understand it. they used AI as a thinking partner, not a replacement for thinking.

the lowest-scoring group did what most people do under deadline pressure: pasted the prompt, copied the output, moved on. they finished fastest.

they learned almost nothing.

and here's the finding that should concern every engineering manager alive: the biggest score gap was on debugging questions.

the skill you need most when supervising AI-generated code is the exact skill that atrophies fastest when you let AI do the work.

the control group made more errors during the task. they hit bugs.

they struggled with async concepts. they got frustrated. and that struggle is precisely what built their understanding.

errors aren't obstacles to learning.
they ARE learning.

removing them with AI removes the mechanism that creates competence.

participants in the AI group literally said afterward they wished they'd "paid more attention" and felt "lazy."

one wrote "there are still a lot of gaps in my understanding."

they could feel the hollowness of having completed something without understanding it.

that's not a productivity win. that's debt.

this paper isn't an argument against using AI. it's an argument against using AI unconsciously.

Anthropic publishing research showing their own product can inhibit skill formation is the kind of intellectual honesty the industry needs more of.

the practical takeaway is simple: if you're learning something new, use AI to ask questions, not to skip the work.

the struggle is the product.

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Thomas W. Gauperaa @gauperaa

4 months ago

@Artedeingenio @Kling_ai I still immediately recognize that ships and buildings are AI generated because they don't make sense, it's just too much of everything, engines, antennas etc etc. Cool video though :)

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